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SIAMIS
2008
141views more  SIAMIS 2008»
13 years 7 months ago
A Nonlinear Inverse Scale Space Method for a Convex Multiplicative Noise Model
We are motivated by a recently developed nonlinear inverse scale space method for image denoising [5, 6], whereby noise can be removed with minimal degradation. The additive noise ...
Jianing Shi, Stanley Osher
JMLR
2012
11 years 9 months ago
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
Avneesh Singh Saluja, Priya Krishnan Sundararajan,...
VLSID
2007
IEEE
120views VLSI» more  VLSID 2007»
14 years 7 months ago
Statistical Leakage and Timing Optimization for Submicron Process Variation
Leakage power is becoming a dominant contributor to the total power consumption and dual-Vth assignment is an efficient technique to decrease leakage power, for which effective de...
Yuanlin Lu, Vishwani D. Agrawal
DAC
2004
ACM
13 years 11 months ago
A methodology to improve timing yield in the presence of process variations
The ability to control the variations in IC fabrication process is rapidly diminishing as feature sizes continue towards the sub-100 nm regime. As a result, there is an increasing...
Sreeja Raj, Sarma B. K. Vrudhula, Janet Meiling Wa...
ICANN
2010
Springer
13 years 8 months ago
Variational Bayesian Image Super-Resolution with GPU Acceleration
With the term super-resolution we refer to the problem of reconstructing an image of higher resolution than that of unregistered and degraded observations. Typically, the reconstru...
Giannis K. Chantas